the use of geographic information system (gis) based

The world will not evolve past its current state of crisis by using the same thinking that created the situation.

Albert Einstein

Complexity is one of the great problems in environmental design.

Christopher Alexander

PAPER NO.

6

Advanced 3D graphics for Geographic Information System (GIS) www.sciencegl.com/gis_dem/index.html

The Use of Geographic

Information System (GIS) Based

Spatial Decision Support

System (SDSS) in Developing

the Urban Planning Process

Khalid S. Al-Hagla

Dept. of Architecture, Faculty of Engineering, Alexandria

University, Alexandria, Egypt

Faculty of Architectural Engineering, Beirut Arab

University, Beirut, Lebanon

Beirut Arab University (BAU), Faculty of

Architectural Engineering.

APJ, Architecture & Planning Journal

20 (2009) 97-115

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http://www.brainyquote.com/quotes/quotes/c/christophe273531.html

http://www.sciencegl.com/gis_dem/index.html

APJ, Architecture & Planning Journal 20 (2009) 97-115

ABSTRACTS

Paper No. 6

1

PAPER NO.6

Online: www.bau.edu.lb

Beirut Arab University (BAU), Faculty of Architectural Engineering.

APJ, Architecture & Planning Journal 20 (2009) 97-115 APJ

The Use of Geographic Information System (GIS) Based

Spatial Decision Support System (SDSS) in Developing the Urban Planning Process

Khalid S. Al-Hagla

Dept. of Architecture, Faculty of Engineering, Alexandria University, Alexandria, Egypt Faculty of Architectural Engineering, Beirut Arab University, Beirut, Lebanon

Abstract

The use of computer-based information systems in the field of planning has been increasingly highlighted with the exploitation of computer technology. Geographic Information Systems (GIS) is the most recognized tool of those Assisting Technological Tolls (ATT), and is well known to the planners, decision makers and other actors of planning episodes as a Decision Support System tool (DSS).

The development of a decision process model using GIS and built upon systematic process of planning is the primary issue of the research. It highlights the planning process as one that incorporates a wide range of knowledge and uses a broad range of data sources. However, these data sources require the establishment of a model to stimulate the interactions among various actors and decision makers and the flow that occurs both at a point in time and over time.

The paper tackles the need for developing an appropriate mechanism that supports decision making – based on a wide range of data inputs- to guarantee the quality of the decision taken. However, it studies the way to meet the need for an urban and regional planning tool based on information technologies which have brought a substantial challenge to the way things are done, accelerating the decision making process and enhancing the process of planning. However, it examines three specific areas of interaction between information technology and urban planning. First; the structure of computer systems used for urban planning, second; the modeling of urban planning data using GIS and, third; the models as the major components of spatial decision support system (SDSS). It highlights the way in which the recent technical developments, mainly using GIS techniques and advanced data modeling have facilitated to a great extent the (SDSS) used in urban planning. © 2009 Beirut Arab University. All rights reserved.

Keywords: Geographic Information System (GIS), Spatial Decision Support System (SDSS), Planning process

سادسالالبحث 1




APJ

The Use of Geographic Information System (GIS) Based Spatial Decision Support System (SDSS) in Developing the

Urban Planning Process

إتخاذ القرار الفراغي المبني علي نظم المعلومات إستخدام نظام دعم الجغرافية في تطوير عمليات التخطيط الحضري

خالد السيد محمد الحجلة/ د - أحمد منير سليمان / د.أ –ريما خير سلطاني / م

لبنان - بيروت -جامعة بيروت العربية –كلية الهندسة المعمارية

الملخص

א א אא א א א א א אא א א Kא אא א

אא‘Geographic Information System (GIS)’ א א א א אא א א א א אא

אאאאאK

אאאאאאאאאאא א א א א א ،אא

א K א אאאאאאאא א

אאאאאאאK

אאאאאאאא א א א

אאאאאא

سادسالالبحث 2

אKאאאאאאאאWא،אאאאא

אאאאאאאאאאאאאאאאאK

אאאאאאאאאאאאאאאאא

אK

The world will not evolve past its current state of crisis by using the same thinking that created the situation.

Albert Einstein

Complexity is one of the great problems in environmental design.

Christopher Alexander

PAPER NO.

6

Advanced 3D graphics for Geographic Information System (GIS) www.sciencegl.com/gis_dem/index.html



Khalid S. Al-Hagla Dept. of Architecture, Faculty of Engineering, Alexandria

University, Alexandria, Egypt Faculty of Architectural Engineering, Beirut Arab

University, Beirut, Lebanon



THE PAPER

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http://www.brainyquote.com/quotes/quotes/c/christophe273531.html�

http://www.sciencegl.com/gis_dem/index.html�

* Corresponding author. E-mail address: [email protected]




APJ



Rima M. Sultani, Ahmed M. Soliman, Khalid S. Al-Hagla *

Faculty of Architectural Engineering, Beirut Arab University, Beirut, Lebanon

Abstract

The use of computer-based information systems in the field of planning has been increasingly highlighted with the exploitation of computer technology. Geographic Information Systems (GIS) is the most recognized tool of those Assisting Technological Tolls (ATT), and is well known to the planners, decision makers and other actors of planning episodes as a Decision Support System tool (DSS).

The development of a decision process model using GIS and built upon systematic process of planning is the primary issue of the research. It highlights the planning process as one that incorporates a wide range of knowledge and uses a broad range of data sources. However, these data sources require the establishment of a model to stimulate the interactions among various actors and decision makers and the flow that occurs both at a point in time and over time.

The paper tackles the need for developing an appropriate mechanism that supports decision making – based on a wide range of data inputs- to guarantee the quality of the decision taken. However, it studies the way to meet the need for an urban and regional planning tool based on information technologies which have brought a substantial challenge to the way things are done, accelerating the decision making process and enhancing the process of planning. However, it examines three specif-ic areas of interaction between information technology and urban planning. First; the structure of computer systems used for urban planning, second; the modeling of urban planning data using GIS and, third; the models as the major components of spatial decision support system (SDSS). It highlights the way in which the recent technical developments, mainly using GIS techniques and advanced data modeling have facilitated to a great extent the (SDSS) used in urban planning. Keywords: Geographic Information System (GIS), Spatial Decision Support System (SDSS), Planning process

1. Introduction

Decision making is a cognitive process leading to the selection of a course of action among a number of alternatives. Every decision making process produces a final choice. It can be an action or an opinion. It be-gins when citizens need to do something but they do not know what. Therefore, decision making is a rea-soning process which can be rational or irrational, and can be based on explicit or implicit assumptions. Therefore, the decision making process is always as-sociated with every phase of the planning process.

However, the process of planning involves many phases and more actors including a process in which activities are defined by conditions in specific areas and by a city’s economic development. Decisions made by different actors in different phases all depend on the information available. (Hall, 1996). However, planning, in its broadest sense, is clearly an activity that requires the use of spatial information in under-taking many core planning activities, including land-use plan formulation (Boddy, 1995)

R. Sultani, A. Soliman, K. Al-Hagla / APJ, Architecture & Planning Journal 20 (2009) 97-115 2

From other stand point, technology in planning is

dictated by what planners do; technology and tech-niques, models and methods, and computations and controls. GIS allows planners to quickly and efficient-ly create and test alternative development scenarios and determines their likely impacts on the future envi-ronment, i.e., land-use patterns and associated popula-tion and employment trends, thus allowing public of-ficials to make informed planning decisions. It uses various techniques for linking policy (aspatial) to plans (spatial) in order to formulate and evaluate spa-tial planning models. Moreover, a large range of spa-tial analysis functions – based on the planning data collected and stored within the GIS database- can be performed to create new information layers. These spatial information layers can be presented in the forms of maps (plans), reports, and charts.

2. Computer Systems Used for Urban Planning

The development of a variety of Decision and Planning Support Systems based on computer tech-nology, and the emergence of Geographical Informa-tion Systems (GIS) are serving to keep the field ac-tively concerned with the use of information technol-ogy. There is very rapid change in that the activity of planning is increasingly pragmatic in its execution (Batty, 1991).The use of GIS as a DSS structure is based on an understanding of both similarities and differences between them. These areas are illustrated in figure 1 as follows:

Figure 1: Graph of an architecture of computer system for urban planning (Laurini, 2001: 38).

- The acquisition model is similar to GIS and DSS. - At output, not only cartographic visualization is

present, but also some graphic tools for exhibit-ing action plans.

- The kernel is similar to that of the DSS, integrat-ing some models to simulate the development of the city together with some evaluation tech-niques, for instance, to estimate the costs and the efficiencies of some planning alternatives.

- The great difference is the presence of additional modules:

• Alternative setting, which can also be present in a DSS; this module is activated by planning officials.

• Groupware management or more precisely, Com-puter Supported Co-operating Work (CSCW) in order to organize and schedule the daily work of the plan-ning staff.

• Management of public participation in order to assist citizens in comparing alternatives, giving their opi-nions, synthesizing them and so on (Laurini, 2001)

Information is the key element in any urban and regional planning process. The data processing sys-tems, i.e., 'Models', offer a vital conceptual framework to understand the role of information systems and of-fer a developed decision making methodology (Lauri-ni, 2001).

Accordingly, it is important to use different model-ing techniques to understand the past or simulate the future; they are especially interested in simulating or forecasting strong trends, and testing assumptions. Different kinds of models could be created (Figure 2):

Figure 2: The structure of the model management system (Laurini, 2001:32).

- Strategic models are used to support strategic

management planning responsibilities; they should be broad in scope and essentially based on external data.

- Tactical models are used mainly by middle man-agement to assist them in their tasks.

- Operational models for daily management.

Several kinds of connections linking a GIS and an urban modeling package can be envisioned as illu-strated in figure 3. Different possibilities can formu-late the relationship between the variables; the case is shown in which the GIS is embedded into the urban modeling package or in contrast the modeling package is embedded into the GIS. Another possibility is to have a loose or a tight coupling between the GIS, the modeling package and the statistical package for the technical reason that the preference is for the tight connections (Laurini, 2001).

Based on different types of connections linking GIS and an urban modeling package, a large number of models and modeling techniques have been devel-

P ublic participantCS CW managementAlternative setting

Data acquisition and updating

Plan formatting and visualization

What i f

models

E valuation

technique

Data management

Database for urban planning

Plannin g officers

Planning staff

Ci ti zens and Other sector

Action plans

M aps

Wri tten regulations


oped to support decision-makers. Many of these are of interest to potential users of spatial decision support systems. These models are drawn from well-established disciplines such as statistics or manage-ment science, and in most cases do not require the use of spatial data. The models in the problem may oper-ate on non-spatial (attribute) data in the SDSS. How-ever the data set to be used for the modeling process may be identified by spatial operations (Keenan, 2004).

Figure 3: Modeling in GIS (Laurini, 2001. p: 33). This fig-ure illustrates the GIS integration with an urban modeling package, i.e., current practices. (a) Embedding a GIS in the modeling package. (b) The reserve. (c) Loose coupling. (d) Tight coupling (Laurini, 2001).

However; planning support systems include the in-

tegration of geographic information with other tech-nologies (e.g. multimedia, models, simulations, and expert systems). Current developments of customized geographic information and other tools only partially respond to analytical, design, administrative, commu-nicative, and the decision-making support needed. The integration of those modules into a functional plan-ning support system and their customization to various planning institutions is yet to be achieved (Nedović-Budić, 2000).

The classic tasks of GIS are the analysis and al-phanumeric/graphic presentation of spatial data. How-ever, the functionality of a conventional GIS can be significantly enhanced by the addition of several new data types. Nedović-Budić (2000), classifies three different groups of data based on data source and for-mat:

- Alphanumeric data; - Vector and raster GIS data; and - Sound, image and video data.

The more advanced "multimedia GIS" is focused

on using vector and raster data. That data core is sup-plemented by alphanumeric, sound, image and video data. However, three main subsequent stages could be identified; data input, data analysis, and data output and presentation.

■ Data Input

At the beginning of the planning process, the availability of digital data should be determined. Spa-tial data can be digitized in various ways; Alphanu-meric data can be recorded using text processing or database software. Vector and raster GIS data can be digitized from orthophotos, maps or sketches (Figure 4). New methodologies have been created to digitize site data directly in the field using portable pen com-puters and geo-referenced background information such as digital maps or orthophotos (Figure 5). Sound, photos and videos can be recorded in the field by means of digital or analogue devices such as standard video recorders and 35mm cameras.

Figure 4: Vector and raster GIS data (http://erg.usgs.gov/isb/pubs/gis_poster/)

Figure 5: Portable pen computers (http://erg.usgs.gov/isb/pubs/gis_poster/)


The spatial accuracy of digitized polygons, points

and lines is one of the most important issues in GIS. Accuracy depends primarily on the quality of the available, basic information. For instance, in addition to the photogram-metric Land-use interpretation based on orthophotos or aerial stereo photo models, the mapping of landscape features from existing paper maps still remains necessary (Figure 6).

Figure 6: City of Cairo inside the ring road. (Example of the raster image) (Stewart et al., 2003).

■ Interactive Data Analysis on Demand

Figure 7: Cairo City (built-up and population /1999) Exam-

ple of Interactive Data Analysis on Demand (Ste-wart et al., 2003).

The ability of GIS to analyze ecological and land-scape-related spatial data has often been discussed and demonstrated. The primary interest is the ability of GIS to do interactive analysis, analysis on demand. Another advantage of using digital data and GIS is the ability to analyze 3-dimensional landscape models which form the basis for visibility, slope, aspect, line-of-sight or watershed calculations. Queries of this na-ture can also be handled, providing the necessary base data is available. Multimedia elements can play an important role in visual analysis. One example here is the ability of GIS to overlay selected thematic maps, allowing the viewer to see complex relationships at a glance. Using this technique, land-use conflicts can be quickly identified and displayed with a level of clarity and legibility that cannot be achieved by analogue cartographic illustrations. Additionally, turning differ-ent map layers on or off can be useful in illustrating the various steps in the planning process.

■ Visualization and Data Presentation

A Master Plan that is easily understood is essential for the acceptance of design proposals. A client-friendly analysis and presentation of planning results has become an important factor in successful plan-ning. A GIS which is able to simulate geo-referenced landscape stimuli is a suitable tool for creating a gen-eral awareness of the relevant planning issues. The various thematic and planning maps are presented as separate "layers" using the ArcGIS software. The vec-tor data-ware ArcInfo coverage’s, ArcView shape files and vectors in Drawing Exchange Format (DXF).

Figure 8: Example Visualization and Data Presentation (http://www.logixml.com)


3. Data Modeling for Urban Planning

The urban planning process is essentially a model-ing process, where planners use models to represent the urban reality and the design intervention within. The urban planning process is where evolution of ur-ban models occurs. The mental models are ideas, theo-ries, and regulations which are processed in the plan-ner’s mind. The urban planning process may not be systematically linear. The planners often use analogue models, such as hand-drawn sketches, or even build a massive model to express their ideas. The ideas and the ruling knowledge are behind the urban planning process which can be systematically represented in the data model as well as the analysis model and design decision model (Putra & Yang, 2003).

A data model has a role, just as digital and analo-gue models do, to represent the mental model. Data modeling is the foundation for the digital modeling in the way that the former becomes the dominating sys-tem of the latter. Unlike analogue and digital models, data models are able to represent not only geometric and functional ideas, but also regulative knowledge, which may be derived from design guidelines.

For example, by running the data model for the "design" part and for the "regulation" part compara-tively and simultaneously, the information system can acknowledge the design "compatibility" with the regu-lation (Putra & Yang, 2003).

On the other hand, most computerized urban plan-ning activities need a spatial database of some kind, where data are stored in a certain format. Through data modeling, a spatial database should be designed to accommodate urban planning analysis and the de-sign decision-making process. A Planning Support System (PSS) usually contains several levels of pre-dictive urban modeling or simulation, which requires a database modeling as the foundation.

Figure 9: A Classification of Models. (Arsham, 2004). Spatial database design is very important in the

development of planning support systems, since a GIS system should be built on standard components. The components start from a spatial database as the foun-dation, then comprise editing, analysis, simulation,

visualization (Pettit, 2002), and finally, making the proposal for the future.

The combination of data modeling in GIS, Spatial Data Engine (SDE), through XML format as a bi-directional medium, provides the potential for manag-ing virtually unlimited amounts of details representing many aspects of the built environment of the entire city, along with different future or past scenarios.

GIS can be used as an integral component for a decision support system (DSS) for managing forest reserves.

Figure 10: The Tisza River Project. In this example, the GIS is used to model the spatial components of the DSS (http://www.tiszariver.com)


Figure 11: Example of a Dynamic Spatial Model (RJC,

2003)

Overall population trends line until year 2025 for the Leinster study area in the Republic of Ireland.

The MOLAND regional model consist of 4 subsystems: Economy, Demography, Land use and Transportation.

Prague, an example. Total cell demands for the industrial landuse class, from 1998 to 2018.

Udine: land use map for 2000 and desktop of the CA software prototype.

Udine: simulation for 2020 using an “optimistic growth” scenario for commercial and residential sparse land use classes.

Udine: current 2000 and simulated simulation for 2020 has been developed using population and economic trends for this city.

Dynamic Spatial Models

A particle modeling framework developed to assist spatial planners and policy makers to analyze a wide range of spatial policies and their associated spatial patterns is presented


3. The Components of SDSS

A decision-support system can be defined as a computer system helping one or more actors in their work of making decisions. DSS provides a mean for decision-makers to make decisions on the basis of more complete information and analysis. Among the main advantages of the use of DSS is an increased number of alternatives examined, a better understand-ing of the business, fast response to unexpected situa-tions, improved communication, cost savings, better decisions, more effective teamwork, time saving, and a better use of data resources.

A particular and important type of DSS is the so-called spatial decision support systems (SDSS). Spa-tial DSS refers to those decision support systems that combine the use of Geographic Information Systems (GIS) technology with software packages for the se-lection of alternatives of location for different activi-ties. GIS provides an important source of tools and techniques, which can usefully be incorporated into a DSS system that makes use of geographic or spatial data.

One of the key components is a 'what-if' model used to simulate the future of the city, for example, according to some assumptions. Among those urban models are the following:

� Transportation and traffic models � Population models � Service and commercial premises locations � Energy and water consumption � Water production, etc.

Figure 12: Structure of a spatial decision-support system

(Laurini, 2001. p: 11). Figure 12 illustrates the main components of a spatial

decision support system (SDSS) which includes (Laurini, 2001):

� Acquisition of strategic information, that is to say information coming from the steering sub-system, (the role of the steering subsystem is to design and make decisions in order to shape the global system and make it evolve towards the desired directions)

together with acquisition of information about the territory under control.

� Acquisition of information about the system to control, that is to say information coming from the controlled system (this sub-system includes all elements for which the decision will be made: it regroups all physical sectors and sociological phe-nomena which can be influenced by decisions) by means of any kind of acquisition techniques or measuring instruments.

� A model of the controlled system, in order to project or forecast evolution; by projection, it means that it is the continuation of the past, all things being equal. If some parameters or assump-tions are changed, one speaks about alternatives and forecasting.

� Modules of what-if models for data and system simulation; the role of this components is to study the data of the past in order to find some regulari-ties for constructing the model. When some per-formance indices exists, it is possible to evaluate and compare the effects of the simulated alterna-tives.

� Visualization of the results; for any alternative, the main variables can be displayed in order to com-pare them visually.

� Action plans; i.e. when an alternative is selected, some action plans should be drawn up and imple-mented (Laurini, 2001).

4. Spatial Decision Support System Aided Urban Planning

Common to all definitions of DSS is a sense that these systems should support a particular type of deci-sion. This characteristic distinguishes DSS from gen-eral purpose management information systems (MIS). While GIS applications may contain the information relevant to a decision, they are usually general purpose systems, not focused on a particular decision. For those types of decision where the standard features of a GIS provide the essential information to the decision maker.

GIS software has proved its ability to provide de-cision support. Many GIS based systems are described as being DSS on the basis that the GIS assisted in the collection or organization of data used by the deci-sion-maker. For many of the current SDSS applica-tions, the main information requirement of the deci-sion-makers is for relatively structured spatial infor-mation. Consequently, the GIS techniques have an important impact on DSS applications (Keenan, 2004).

For the full range of problem areas where GIS techniques can make an important contribution, par-ticular problem related models are needed to fully support decisions. For these areas at least, a standard GIS cannot be said to be a DSS because such a system lacks the support that the use of customized models


can provide. For this wide range of second order uses of spatial data, additional processing or integration with non-spatial models is required to fully support the decision maker.

Table 1: The functions of SDSS (Maczewski, 1997)

A number of modules has to be identified to ex-tend the present use of a GIS as a DSS, (Keenan, 2004) as follows:

� Data Entry Module: This module is for entering basic geographic and attributes data. Data control module is also entered using this module.

� Assessment Module: This is used to develop various sub-modules which will be used to support the development module.

� Development Module: This module is used to develop the predictive models for any pollutant at any location.

� Control Module: This module is important for decision-makers and it is used to control the pollution level of criteria pollution. Various regulations and policies are a part of this module.

� User-Interface: Consists of menu-based inter-face to help various planners and decision-makers in efficient usage of the development DSS.

All the modules should be well linked together within a GIS-based user interface and should provide graphics, dialog boxes, spatial analysis and, other re-quired functions (Agrawal et al., 2003).

Figure 13: The structure of proposed GIS-Based DSS (Agrawal et al. 2003).

GIS software provides an interface for spatial in-formation and a database support that is designed to allow for the effective storage of spatial data. Fur-thermore it provides a link between the interface and database to allow the user to easily query spatial data (Keenan, 2004).

Figure 14: Loose (a) and tight (b) MC-SDSS coupling Strat-egies (Maczewski, 1999).

Figure 15: Building a SDSS by integrating models with GIS (Sprague, 1980).

Components Functions

Dat

a B

ase

and

Man

agem

ent Types of data.

Locational (e.g. coordinates), topological (e.g. points, lines, polygons and relationships between them), and attributes (e.g. geology, elevation, transportation network). Logical Data Views - Relational DBMS, hierar-chical DBMS, network DBMS, and object-oriented DBMS. - Management of Internal and External Databases. Acquisition, storage, retrieval, manipulation, di-rectory, queries, and integration.

Mod

el B

ase

and

Man

agem

ent

Analysis - Goal seeking, optimization, simulation, and what-if. Statistics and forecasting. Exploratory spatial data analysis, confirmatory spatial data analysis, time series, and geostatistics. - Modeling decision maker's preference. Value structure, hierarchical structure of goals, evaluation criteria, objectives and attributes, pair-wise comparison, multiattribute value/utility, and consensus modeling. Modeling uncertainty - Data uncertainty, decision rule uncertainty, sensitivity analysis, and error propagation analysis.

Dia

log

Man

agem

ent

User friendliness - Consistent, natural language comments, help and error messages, and novice and expert mode.. Variety of dialog styles. Command lines, pull-down menus, dialogue box-es, and graphical user interfaces. Graphical and tabular display - visualization in the decision space (high-resolution cartographic displays), visualization in the decision outcome space (e.g. two and three-dimensional scatter plots and graphs, tabular rapports).


Data Input & Processing Data Analysis Output DataDisplay Visualization

Missio

n S

tatemen

tS

et Go

als & O

bjectives

Develo

pm

ent

Mo

nito

ring

GIS Operations

Ratio

nal p

lann

ing

pro

cessProposals

Defin

e the p

rob

lem

Determ

ine C

riteria Evalu

atio

n

Weig

ht C

riteria Alte

rnatives

Ap

ply D

ecision

Ru

le

Reco

mm

end

the b

est So

lutio

n

DSS

DSS

Figure 16: The interaction between the GIS, Planning Process and Decision Support System (the authors)

There are four different domains in which SDSS can make a contribution to decision making (Keenan, 2004).

First: in the traditional areas of application of GIS, in disciplines such as geology, forestry, and land plan-ning. In these fields GIS was initially used as a means of speeding up the processing of spatial data, for the completion of activities that contribute directly to productivity. In this context the automated production of maps, in these disciplines, has a role similar to that of data processing in planning.

Second: in fields such as routing or location anal-ysis. The spatial component of such decisions is clear, however, these models are incorporated into GIS based SDSS, providing superior interface and data-base components to work with the models. This syn-thesis of management science and GIS techniques provides more effective decision making. Simpler and less effective integration of models only allows the modeling routines access to the non spatial data. Full integration requires that model routines be able to make use of all the features of GIS (Sprague, 1980).

Third: in disciplines such as marketing, where ad-ditional possibilities for analysis are provided by the availability of increasing amounts of spatially corre-lated information, for example demographic data. Fur-thermore, the geographic convenience of product supply relative to customers' locations is an important tool of market driven competition. The availability of user friendly SDSS to manipulate this type of data leads to additional decision possibilities being ex-amined which are difficult to evaluate without the use of such technology.

Table 2: Computerized Support for Decision Making (Laurini, 2001).

Fourth: in decision making for sustainable devel-opment, GIS can provide decision-makers with useful information by means of analysis and assessment of spatial database (Figure 6.16). Driving forces include population growth, health and wealth, technology, politics, economics etc., by which human society will set up targets and goals on how to improve the quality of life (www.metu.edu.tr).

Phas

e

Description Traditional Tools

Spatial Tools

Ear

ly Computes,

"crunches num-bers", summariz-es and organizes.

Early computer programs, man-agement science models.

Computerized cartography.

Inte

rmed

iate

Finds, organizes and displays decision relevant information

Database man-agement sys-tems, MIS.

Workstation GIS.

Cur

rent

Performs deci-sion relevant computations on decision relevant information; organizes and displays the results. Query based and user friendly ap-proach. "What If" analysis.

Financial mod-els, spreadsheets, trend explora-tion, operations research models, decision support systems.

Spatial decision support systems.


Thus human driving forces, the key elements of

human dimensions, will give impacts on the environ-ment in areas such as development of natural re-sources, urbanization, industrializations, construction, energy consumption etc. Remote sensing can be very useful for a better understanding of the relationship between human impacts and environmental change as well as for building databases. Physical dimensions monitored by remote sensing can be fed back to hu-man dimensions through analysis and assessment by GIS in order to support better decisions (www.metu.edu.tr).

Figure 16: GIS for Decision Support (www.metu.edu.tr).

Conclusion

This paper discusses the role of information tech-nology in developing the computer based systems used for supporting decision making. It reviews –conceptually- different computer system used in urban planning, highlighting the qualities of Geographical Information Systems (GIS) as a DSS structure. More-over, it reviews the development of Decision and Planning Support System, urban modeling and GIS, and the role of GIS in urban planning.

In addition, the paper emphasizes the role of data as the cornerstone in GIS and planning, and it dis-cusses both the development and the role of data mod-eling in urban planning. Furthermore, it analysis the potentials of GIS as a concept that has the capacity to integrate information from a variety of sources into a

spatial context that is well suited to support decision making procedures. That helps the decision-makers evaluate alternatives, visualize choices and explore certain alternatives.

Given the advances in computer technology in general and GIS techniques in particular, this chapter summarizes that SDSS is an important component of DSS applications. This trend is driven by the relev-ance of spatial information as a component of the in-formation needed for a wide range of decisions. This class of DSS makes an important contribution because it allows decision makers to incorporate a spatial di-mension into their decision making, in addition to its use of the latest technology. This spatial dimension, which is not fully catered for in traditional DSS de-signs, is an important feature of many areas of DSS application.

On the other hand, comprehensive decision sup-port requires the effective integration of GIS and non GIS techniques. The building of SDSS applications from GIS has been facilitated by recent technical de-velopments, both within GIS software, and generally, in programming tools.

References

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